As a technique of improving the quality of a color image captured by a color image capturing device, various techniques of making the color of a specific object (for example, flesh color, green of plants, and a blue sky) in a color image closer to the memory color of the object have been proposed. The use of these methods enables desirable colors to be reproduced.
For example, Patent Literature 1 discloses a technique of correcting the color of color images. In an automatic color correction method disclosed in Patent Literature 1, a representative color is extracted from a correction target area in an image, and the representative color is compared with a predetermined central color for correction to determine RGB correction parameters. Moreover, each pixel is corrected by controlling application strength of the correction parameters according to the distance between the pixels in the image and the central color.
Specifically, in the method disclosed in Patent Literature 1, the hue, saturation, and lightness of the respective pixels are calculated from the RGB values which are the color information of the respective pixels. Moreover, the distance between the color of each pixel in a color space and the central color for correction is calculated, and the correction strength is adjusted according to the distance. In this way, the color of an object is intensively corrected.
In this technique, color correction is performed based on the addition and subtraction of correction parameters in the RGB color space. For example, in the case of flesh color of a human face, the RGB correction amount is calculated for each pixel according to the distance between each color and the central color for correction. If the whole face area is lightened, a correction parameter corresponding to the distance from the central color for correction is added to or subtracted from the RGB values of each pixel located in substantially the entire face area.
Patent Literature 2 discloses a technique of detecting a face area in an input image. According to an eye detection method disclosed in Patent Literature 2, even if it is not possible to discriminate eyes from the other portions due to deficient features when a single eye is evaluated, the eyes and the other portions are discriminated using an evaluation value of a pair of eyes based on the features of the pairs of eyes.
In addition to the above patent literatures, Patent Literatures 3 to 5 disclose techniques related to color image correction processes. Patent Literature 3 discloses a color correction device and method in which when color correction is performed on image data of spectral colors, the color space of the spectral colors is converted into a color space having a lower dimension than the original dimension, color correction is performed in the low-dimensional color space, and spectral colors of an appropriate dimension are generated from the spectral colors of the lower dimension.
Patent Literature 4 discloses a color conversion method of converting an original color space into a target color space between color systems having different reference white colors without changing the way in which colors are viewed. Specifically, in the color conversion method disclosed in Patent Literature 4, the spectral distribution characteristics of the original reference white color are reconstructed from the color temperature of the original reference white color which is the reference white color of the original color space. Moreover, the spectral distribution characteristics of the target reference white color are reconstructed from the color temperature of the target reference white color which is the reference white color of the target color space. Further, the surface reflectance of an optional color in the original color space is reconstructed using the tristimulus values of the optional color, the spectral distribution characteristics of the original reference white color, and the color matching functions of the human beings. Furthermore, the tristimulus values which are the colors in the target color space are obtained based on the reconstructed surface reflectance, the reconstructed spectral distribution characteristics of the target reference white color, and the color matching functions of the human beings.
Patent Literature 5 discloses a technique of automatically performing favorable color correction with respect to an important subject in an image of the nature, captured under various illumination environments. Specifically, in the color correction method disclosed in Patent Literature 5, a body surface color of a specific object is extracted, and optimal color correction parameters are set for the extracted body surface color. Color correction conversion that is applied to only a specific color is performed using the parameters. By performing such conversion, it is possible to automatically perform color correction with respect to an important subject in the image of the nature captured under various illumination environments.
Moreover, Patent Literature 6 discloses a technique of generating a skin reflection model of a human face to apply the model to rendering of a facial image. In the method disclosed in Patent Literature 6, first, the human face is scanned using a 3D scanner to acquire a 3-dimensional shape. In this case, a plurality of facial images is acquired by illuminating the face from different directions and different viewpoints. Moreover, a total reflectivity and a normal map are estimated using the surface scan data and the image data. Moreover, the total reflectivity is divided into two components of an under-surface scattering component and a (specular) surface reflection component, and a diffusion reflection is estimated based on these components. Further, the under-surface reflection is scanned using a fiber-optic spectrometer to obtain a transmittance map.
In Patent Literature 7, an image processing method is disclosed in which a pixel value of each pixel configuring an image is divided into a surface reflection light component according to surface reflection on a 3-dimensional object and a diffused reflection light component according to diffuse reflection, and at least one of the surface reflection light component and the diffused reflection light component is changed. In the image processing method disclosed in Patent Literature 7, a reflection model is divided into a surface reflection light component and a diffused reflection light component using a reflection model (hereinafter, referred to as a Klinker's division method) of Klinker and the others. Then, each divided reflection component is changed by using a Phong illumination model, a Lambertian reflection model, or the like.
Further, Non Patent Literature 1 discloses a face detection method using generalized learning vector quantization. Moreover, Non Patent Literature 2 discloses a face detection method using generalized learning vector quantization in which an image-based face detection method and a feature-based face detection method of detecting eye are combined.
Moreover, as a method of obtaining a 3-dimensional shape of the face, in addition to the method that uses a 3D scanner disclosed in Patent Literature 6, a method of reconstructing the face information of a 3-dimensional shape (3-dimensional information) from a 2-dimensional facial image is also known (for example, Non Patent Literature 3).
The contents disclosed in Patent Literatures 1 and 2 and the contents discloses in Non Patent Literatures 1 to 2 are appropriately referenced in the exemplary embodiments of the present invention.